Described processes include: obtaining a first amount of cryptographic tokens transferred to burn addresses by members of a first set of entities; determining a second amount of instances of the first type of cryptographic token to be minted; determining portions of the second amount of instances of the first type of cryptographic token to be allocated to members of a second set of entities, wherein: the portions are determined based on effects determined to be caused by members of the second set of entities on performance of a computer-implemented network in which both the first set of entities and the second set of entities participate, and the effects on network performance are quantified by metrics reported by members of the first set of entities; appending to the first distributed ledger, records indicating the respective portions are transferred to respective accounts of corresponding members of the second set of entities.
Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A tangible, non-transitory, machine-readable medium storing instructions that when executed by one or more processors effectuate operations comprising: obtaining a utilization graph, the utilization graph being based on which content-consumers access which content items, the utilization graph having: nodes indicative of respective ones of the content items available on a content-distribution platform, each of the content items being associated in memory with one of a plurality of different content-contributors credited with making the respective one of the content items available, and edges indicative of access of which ones of the content items by the content-consumers; selecting, from a distributed ledger of a distributed computing platform, a set of records indicative of transactions in which amounts of instances of a cryptographic token are transferred to a burn address of the distributed ledger, at least some transactions being associated with an indication of a respective content-consumer being permitted to access one or more of the content items as a result of a transaction; determining, based on the utilization graph, a network-effect score for each node in a set of nodes accessed by the content-consumers indicated in association with the at least some transactions in the set of records; determining, for each of at least some of the different content-contributors, an aggregate network-effect score for the content-contributor, the aggregate network-effect score being based on network-effect scores of nodes, in the set of nodes, corresponding to the respective ones of the content items the content-contributor is credited with making available; determining portions of an amount of new instances of the cryptographic token to allocate to the different content-contributors based on the respective aggregate network-effect scores; and causing, after determining the portions, the distributed computing platform to record, by appending to the distributed ledger in accordance with a consensus protocol executed by participant computing nodes of the distributed computing platform, one or more records indicating that the respective portions of the amount of new instances of the cryptographic token are, or are to be, added to respective accounts documenting contributions of the respective content-contributor to the content-distribution platform.
This invention relates to a system for distributing cryptographic tokens to content contributors on a content-distribution platform based on network effects. The system addresses the challenge of fairly compensating contributors whose content generates significant engagement and value within the platform. The solution involves analyzing a utilization graph that maps content items to their consumers, where nodes represent content items and edges represent access patterns. The system selects transaction records from a distributed ledger, identifying transactions where cryptographic tokens are burned (transferred to a burn address) to grant access to content. For each accessed content item, a network-effect score is calculated based on its position and influence within the utilization graph. Contributors are then assigned aggregate network-effect scores by summing the scores of their associated content items. These scores determine the allocation of newly minted tokens, which are distributed proportionally to contributors' accounts on the ledger. The system ensures transparent and automated compensation by recording the allocations on the distributed ledger via consensus protocols. This approach incentivizes contributors to create high-value content that drives platform engagement.
2. The medium of claim 1 , wherein: a plurality of nodes in the utilization graph are associated with a given content-contributor to credit the given content-contributor with making a corresponding plurality of the content items available; and nodes or edges are added to the utilization graph based on determinations that one or more of the corresponding plurality of the content items were each accessed for more than a threshold duration of time.
This invention relates to a system for tracking and crediting content contributors based on user engagement with their content. The system generates a utilization graph that maps relationships between content items, contributors, and user interactions. Nodes in the graph represent content items, contributors, or other entities, while edges represent relationships such as contributions, access, or sharing. The invention enhances this graph by associating multiple nodes with a single content-contributor to credit them for making multiple content items available. Additionally, nodes or edges are dynamically added to the graph when content items are accessed for more than a predefined threshold duration, indicating meaningful engagement. This approach ensures that contributors are credited proportionally to the actual usage of their content, improving fairness in attribution. The system may also analyze the graph to identify influential contributors or popular content, enabling better content recommendations or contributor recognition. The invention addresses the challenge of accurately measuring and rewarding content contributions in digital platforms where engagement varies widely.
3. The medium of claim 1 , wherein: an edge between a pair of different ones of the nodes in the utilization graph indicates sequential access of respective ones of the content items during a session in which at least two of the content items were accessed by one of the content-consumers; the set of nodes accessed by the content-consumers indicated in association with the at least some transactions in the set of records comprises a first node corresponding to a first one of the at least two content items and a second node corresponding to a second one of the at least two content items; and determining network-effect scores of the first and second node comprises: determining a measure of network centrality of the first node relative to that of the other nodes in the set of nodes; and determining a measure of network centrality of the second node relative to that of the other nodes in the set of nodes.
This invention relates to analyzing content consumption patterns using network analysis techniques. The problem addressed is identifying influential content items within a network of user interactions, where content items are represented as nodes and relationships between them are derived from sequential access patterns during user sessions. The system constructs a utilization graph where edges between nodes indicate that one content item was accessed immediately before another in a user session. The graph includes nodes representing content items and edges representing sequential access relationships. To assess the influence of specific content items, the system calculates network-effect scores by determining the network centrality of each node relative to others. Network centrality measures how connected or influential a node is within the graph, helping identify which content items are most frequently accessed in sequence or act as hubs in user navigation paths. This analysis helps prioritize content based on its role in user engagement, improving content recommendation systems or identifying key content items for marketing or curation purposes. The method involves processing transaction records to extract sequential access patterns, constructing the utilization graph, and computing centrality metrics to derive the network-effect scores.
4. The medium of claim 1 , wherein: the utilization graph indicates access of a subset of the content items by a plurality of the content consumers; the utilization graph is formed with operations comprising: obtaining a plurality of sequences in which respective ones of the plurality of the content-consumers accessed one or more of the content items in the subset; determining a transition probability matrix between the content items in the subset based on the plurality of sequences; and determining the edges of the utilization graph based on whether values of the transition probability matrix, or values based thereon, satisfy a threshold; and the aggregate network-effect score for a given content-contributor is representative of value added to the content-distribution platform by the given content-contributor among other ones of the content-contributors over at least the selected set of records.
This invention relates to a system for analyzing content consumption patterns on a content-distribution platform to evaluate the influence of content contributors. The problem addressed is the need to quantify the value added by individual contributors based on how their content is accessed and shared among users. The system generates a utilization graph representing how users navigate between content items, where edges in the graph are determined by transition probabilities derived from user access sequences. If these probabilities exceed a predefined threshold, connections between content items are established in the graph. The transition probabilities are calculated by analyzing sequences in which users access multiple content items, and the resulting matrix is used to identify significant relationships. The system also computes an aggregate network-effect score for each contributor, reflecting their impact relative to others by measuring the value they bring to the platform through user engagement with their content. This score helps assess the influence of contributors beyond simple metrics like view counts, considering how their content drives broader platform activity. The approach enables platforms to identify high-value contributors and optimize content distribution strategies.
5. The medium of claim 1 , wherein: the utilization graph indicates access of a subset of the content items by a plurality of the content consumers; the utilization graph is formed with operations comprising: obtaining a plurality of records each indicating which ones of the content items were accessed by a respective one of the content-consumers; determining co-occurrence rates in the plurality of records, the co-occurrence rates indicating access of pairs of the content items indicated in the records; determining the edges of the utilization graph based on whether the co-occurrence rates or values based thereon satisfy a threshold; and the aggregate network-effect score for a given content-contributor is representative of value added to the content-distribution platform by the given content-contributor among other ones of the content-contributors over at least the selected set of records.
This invention relates to analyzing content consumption patterns on a content-distribution platform to assess the value of individual content contributors. The problem addressed is determining how much value a specific contributor adds to the platform by measuring the network effects of their content, particularly how their content is accessed alongside others. The system generates a utilization graph representing content access patterns. This graph is constructed by collecting records of content accessed by multiple users, analyzing these records to identify co-occurrence rates of content items (i.e., how often pairs of items are accessed together), and forming edges in the graph based on whether these co-occurrence rates meet a predefined threshold. The graph visually maps relationships between content items based on user access behavior. An aggregate network-effect score is then calculated for each content contributor, quantifying their impact relative to others. This score reflects the value they contribute to the platform by influencing how their content interacts with other content, as observed in the utilization graph. The analysis is performed over a selected set of records, ensuring the score is based on relevant data. This approach helps platforms identify high-value contributors and optimize content distribution strategies.
6. The medium of claim 1 , further comprising: receiving a registration request from a computing device of a given content-contributor; establishing, in response to the registration request, a record of the given content contributor indicating a cryptographic hash based account of the given content-contributor to which a corresponding portion of the new instances of the cryptographic tokens are, or are to be, added; associating a given content item added to the content-distribution platform by the given content-contributor with the record of the content-contributor, wherein: the given content item is cryptographically signed with a private-cryptographic key of the given content-contributor before being uploaded to the content-distribution platform; and a given node corresponding to the given content item available on the content-distribution platform is caused to comprise an identifier indicative of the given content-contributor of the given content item after validating the cryptographic signature with a public cryptographic key associated with the identifier of the given content-contributor.
This invention relates to a content-distribution platform that manages cryptographic tokens and content contributions from multiple contributors. The system addresses the challenge of securely verifying and associating content with its contributors while ensuring traceability and integrity. The platform receives registration requests from computing devices of content-contributors, establishing records for each contributor that include a cryptographic hash-based account. These accounts are used to track portions of cryptographic tokens assigned to the contributor. When a contributor uploads a content item, the system associates the item with the contributor's record. The content item is cryptographically signed with the contributor's private key before upload. Upon receiving the item, the platform validates the signature using the contributor's public key and associates the content with the contributor's identifier. This ensures that only authenticated content is linked to the correct contributor, maintaining trust and accountability in the distribution process. The system leverages cryptographic techniques to prevent unauthorized modifications and ensures that content provenance is verifiable.
7. The medium of claim 1 , wherein: the utilization graph is constructed based on utilization data indicative of access of a plurality of the content items over a network; and the operations further comprise: establishing nodes of the utilization graph based on identifiers of the plurality of the content items represented within the utilization data; establishing edges between pairs of at least some of the nodes within the utilization graph based on one or more sequences of occurrence of the identifiers; and scoring indications of access of each content item within the plurality of the content items by the computing device based on criteria satisfied by one or more of properties of the utilization data or properties inferred from the utilization data.
This invention relates to analyzing content item access patterns over a network to generate a utilization graph. The problem addressed is the need to understand relationships between content items based on how users access them, enabling improved content recommendations or network optimization. The system constructs a utilization graph where nodes represent content items identified by unique identifiers from network access data. Edges between nodes are established based on sequences in which these identifiers appear, reflecting how users navigate between content items. The graph is built using utilization data that tracks access patterns, such as timestamps, user interactions, or network requests. Additionally, the system scores each content item's access indications based on criteria derived from the utilization data or inferred properties. These criteria may include frequency of access, temporal patterns, or inferred user preferences. The scoring helps prioritize or rank content items for recommendations, caching, or other network management tasks. By analyzing sequences of access and scoring content items, the system provides insights into user behavior and content relationships, improving content delivery or recommendation systems. The utilization graph and scoring mechanism enable dynamic adaptation to changing access patterns.
8. The medium of claim 1 , wherein determining a network score for each node in the set of nodes or an aggregate network score for each of the at least some of the different content-contributors comprises: determining a measure of network centrality based on an eigencentrality of corresponding nodes in the set of nodes determined with power iteration based on an adjacency matrix of the utilization graph.
This invention relates to analyzing network structures, particularly for evaluating content-contributors within a network. The problem addressed is the need to assess the influence or importance of nodes (e.g., content-contributors) in a network by quantifying their centrality. Traditional methods may not accurately capture the dynamic relationships and influence within the network. The invention involves determining a network score for nodes or groups of nodes by calculating a measure of network centrality. Specifically, it uses eigencentrality, a metric that evaluates the importance of a node based on its connections to other important nodes. The eigencentrality is computed using power iteration, an iterative algorithm applied to an adjacency matrix derived from a utilization graph. The utilization graph represents the relationships or interactions between nodes, where the adjacency matrix encodes these connections. Power iteration is used to approximate the principal eigenvector of the adjacency matrix, which reflects the centrality of each node. This approach provides a scalable and computationally efficient way to assess node importance, particularly in large or complex networks. The resulting network scores can be used to rank or prioritize content-contributors based on their influence within the network.
9. The medium of claim 1 , wherein determining a network score for each node in the set of nodes or an aggregate network score for each of the at least some of the different content-contributors comprises: determining a measure of network centrality based on a percolation centrality of corresponding nodes in the set of nodes.
This invention relates to analyzing social networks or other interconnected systems to assess the influence or importance of nodes (e.g., users, content-contributors) within the network. The problem addressed is the need for an accurate and computationally efficient method to quantify the significance of nodes based on their connectivity and influence patterns, particularly in large-scale networks where traditional centrality measures may be impractical. The invention involves determining a network score for individual nodes or groups of nodes (e.g., content-contributors) by calculating a measure of network centrality. Specifically, it uses percolation centrality, a metric that evaluates how critical a node is to the network's overall connectivity and information flow. Percolation centrality assesses the likelihood that a node acts as a bridge or hub, ensuring robust connectivity even if other nodes are removed. This approach helps identify influential nodes that are essential for maintaining network integrity or spreading information. The method can be applied to various network types, including social media platforms, communication networks, or collaborative systems, where understanding node importance is crucial for tasks like influence analysis, recommendation systems, or network resilience assessment. By leveraging percolation centrality, the invention provides a more nuanced and reliable measure of node importance compared to traditional centrality metrics like degree or betweenness centrality.
10. The medium of claim 1 , wherein determining a network score for each node in the set of nodes or an aggregate network score for each of the at least some of the different content-contributors comprises: determining a measure of network centrality is based on node2Vec embeddings of corresponding nodes in the set of nodes.
This invention relates to analyzing social or information networks to assess the influence or importance of nodes (e.g., users, content-contributors) within the network. The problem addressed is the need for an objective, data-driven method to quantify the centrality or importance of nodes in a network, which is useful for tasks like identifying influential users, detecting key contributors, or understanding information flow. The invention involves determining a network score for individual nodes or aggregate scores for groups of nodes (e.g., content-contributors) by leveraging node2Vec embeddings. Node2Vec is an algorithm that generates low-dimensional vector representations of nodes in a network, capturing structural properties like connectivity and proximity. The network score is derived from these embeddings to measure network centrality, which reflects a node's importance based on its position and connections within the network. This approach provides a scalable and computationally efficient way to assess node importance, improving upon traditional centrality metrics that may not account for complex network structures. The method can be applied to various network types, including social networks, collaboration networks, or content-sharing platforms, where understanding node influence is critical. By using node2Vec embeddings, the invention captures both local and global network properties, enabling more accurate and nuanced centrality measurements. This enhances applications like recommendation systems, fraud detection, or community analysis by identifying key nodes more effectively.
11. The medium of claim 1 , wherein: the network-effect score for each node in the set of nodes is based in part on content-consumer input scores of different ones of the content-consumers represented within the set of records; and a content-consumer input score of a given content-consumer is based in part on an amount of instances of the cryptographic token transferred to the burn address by one or more transactions associated with an indication of the given content-consumer.
This invention relates to a system for evaluating nodes in a network based on cryptographic token transactions, particularly focusing on content-consumer interactions. The system calculates a network-effect score for each node by analyzing content-consumer input scores derived from cryptographic token transfers. Specifically, the score for a given content-consumer is determined by the number of instances of a cryptographic token transferred to a burn address in transactions linked to that consumer. The burn address serves as a mechanism to permanently remove tokens from circulation, and the frequency of such transfers indicates the consumer's engagement or influence within the network. The network-effect score aggregates these input scores to assess the overall impact or value of each node. This approach enables the system to quantify the influence of content-consumers based on their token-burning activity, providing a measurable metric for network dynamics. The invention is particularly useful in decentralized systems where token transactions are used to gauge user participation and contribution.
12. The medium of claim 11 , wherein a transaction associated an indication of the given content-consumer corresponds to: subscription access to the content-distribution platform by the given content-consumer, subscription access to a subset of content items on the content-distribution platform by the given content-consumer, or a purchase corresponding to one or more of the content items on the content-distribution platform by the given content-consumer.
A content-distribution platform manages access to digital content items for consumers. The platform tracks transactions associated with content-consumers, where each transaction indicates a type of access granted to the consumer. The access types include full subscription access to the entire platform, partial subscription access to a subset of content items, or a purchase of one or more specific content items. The platform uses these transaction indicators to determine the consumer's access rights and permissions. This system allows for flexible content distribution models, enabling consumers to choose between different access tiers or individual purchases. The platform may also use these transaction records to analyze consumer behavior, optimize content recommendations, or enforce access restrictions. The invention improves content distribution by providing clear, transaction-based access control mechanisms that adapt to various consumer preferences and business models.
13. The medium of claim 1 , wherein appending one or more records to the distributed ledger in accordance with a consensus protocol executed by participant computing nodes of the distributed computing platform comprises: agreement upon a prior version of the distributed ledger comprising the set of records and other prior records by a majority of the participant computing nodes; and agreement upon a new version of the distributed ledger comprising the one or more appended records.
A distributed ledger system is used to maintain a shared, tamper-resistant record of transactions or data across multiple computing nodes. A challenge in such systems is ensuring consistency and reliability when new records are added, as nodes may have different versions of the ledger or disagree on updates. This invention addresses this problem by defining a consensus-based method for appending records to a distributed ledger. The system involves a distributed computing platform with multiple participant nodes that collectively manage the ledger. To append new records, the nodes first reach consensus on the current state of the ledger, which includes all previously agreed-upon records. This ensures that all nodes start from the same baseline. Once consensus is achieved on the prior version, the nodes then agree on a new version of the ledger that includes the newly appended records. The consensus protocol requires a majority of the participant nodes to approve both the prior and new versions, ensuring that updates are validated and synchronized across the network. This approach prevents conflicts and maintains the integrity of the distributed ledger.
14. The medium of claim 13 , wherein: agreement upon the new version of the distributed ledger is dependent on agreement upon the prior version and a plurality of other prior versions of the distributed ledger, an alteration of a given prior version of the distributed ledger renders a change in a cryptographic hash value based on the given prior version, and agreement upon the new version of the distributed ledger is dependent on verification that cryptographic hash values based on the prior versions are unchanged.
This invention relates to distributed ledger technology, specifically ensuring data integrity and consensus in a decentralized system. The problem addressed is maintaining consistency and preventing unauthorized modifications in a distributed ledger where multiple participants must agree on updates. The solution involves a method where agreement on a new version of the ledger depends not only on the immediately prior version but also on multiple other prior versions. This creates a dependency chain that enhances security. Any alteration to a prior version of the ledger changes its cryptographic hash value, which is derived from the content of that version. Agreement on the new version requires verifying that the cryptographic hash values of all relevant prior versions remain unchanged, ensuring that no prior data has been tampered with. This multi-version verification mechanism strengthens the integrity of the ledger by making it difficult for an attacker to alter past data without detection. The system ensures that consensus is only achieved if all referenced prior versions are unaltered, providing a robust defense against unauthorized modifications.
15. The medium of claim 1 , wherein appending to the distributed ledger in accordance with a consensus protocol executed by participant computing nodes of the distributed computing platform, one or more records indicating that the respective portions of the amount of new instances of the cryptographic token are, or are to be, added to respective accounts documenting contributions of the respective content-contributor to the content-distribution platform comprises: appending, by a script executed by one or more of the participant computing nodes of the decentralized computing platform, to the distributed ledger, the one or more records indicating the respective portions are transferred to the respective accounts by one or more transactions identifying respective cryptographic hash-based addresses of the content-contributors.
This invention relates to a distributed ledger system for tracking contributions to a content-distribution platform using cryptographic tokens. The problem addressed is the need for a transparent and secure method to document and reward contributions from multiple content-contributors in a decentralized manner. The system involves a distributed computing platform where participant computing nodes execute a consensus protocol to append records to a distributed ledger. When new instances of a cryptographic token are generated, the system allocates portions of these tokens to content-contributors based on their contributions. These allocations are recorded as transactions in the distributed ledger, specifying the cryptographic hash-based addresses of the contributors' accounts. The transactions ensure that the token portions are transferred to the respective accounts, documenting the contributors' contributions to the platform. The use of a decentralized computing platform and cryptographic hashing ensures that the allocation and transfer of tokens are tamper-proof and verifiable by all participants. This method provides a transparent and automated way to reward contributors while maintaining the integrity of the ledger through consensus mechanisms. The system is particularly useful in environments where decentralized verification and secure tracking of contributions are essential.
16. The medium of claim 1 , wherein selecting, from a distributed ledger of a distributed computing platform, a set of records indicative of transactions in which amounts of instances of a cryptographic token are transferred to a burn address of the distributed ledger comprises: selecting a set of burn transactions associated with a current mint period of the cryptographic token from the set of records, the amount of new instances of the cryptographic token being minted for the current mint period in response to a determination that the set of burn transactions satisfy mint criteria for the current mint period, wherein: a burn transaction takes instances of the cryptographic token out of circulation by transferring the instances of cryptographic tokens to a burn address inoperable to transfer received instances of the cryptographic token to other addresses on the distributed computing platform, and the set of burn transactions associated with the current mint period have an aggregate score meeting or exceeding a target score for the current mint period based on amounts of instances of the cryptographic token being taken out of circulation in one or more prior mint periods.
This invention relates to a system for managing cryptographic tokens in a distributed ledger, specifically focusing on token burning and minting mechanisms. The problem addressed involves ensuring controlled issuance of new tokens based on prior burn transactions, where tokens are permanently removed from circulation by transferring them to a burn address that cannot transfer them further. The system selects burn transactions from a distributed ledger associated with a current mint period, where the aggregate value of burned tokens meets or exceeds a target score. This score is determined based on the amounts of tokens burned in one or more prior mint periods. If the burn transactions satisfy predefined mint criteria for the current period, new tokens are minted accordingly. The burn address is inoperable to transfer received tokens, ensuring they are permanently removed from circulation. This mechanism links token supply adjustments to historical burn activity, promoting stability and predictability in token issuance. The system operates within a distributed computing platform, leveraging the immutability and transparency of the ledger to enforce the minting rules.
17. The medium of claim 1 , wherein: the content items are physical goods, the content-contributors provide the goods to the content-distribution platform, the content-distribution platform includes a delivery network in which drivers deliver physical goods to various geolocations to execute tasks assigned to the drivers by the content-distribution platform, the edges indicative of access of which ones of the content items by the content-consumers indicate which physical goods are delivered or scheduled for delivery to the content-consumers, and at least some network effect scores are determined for respective drivers based on an amount of tasks assigned to the drivers by the content-distribution platform.
A system for managing the distribution of physical goods through a delivery network involves a content-distribution platform that facilitates the movement of goods from contributors to consumers. The platform assigns delivery tasks to drivers, who transport the goods to various geolocations. The system tracks which goods are accessed by consumers, indicating whether they have been delivered or are scheduled for delivery. Additionally, the platform calculates network effect scores for drivers based on the volume of tasks assigned to them, reflecting their activity and efficiency within the delivery network. This approach optimizes logistics by leveraging data on driver performance and delivery patterns to improve distribution processes. The system ensures that goods are efficiently routed and delivered while monitoring driver productivity through task assignments. By analyzing delivery data and driver metrics, the platform enhances operational efficiency and resource allocation in the distribution network.
18. The medium of claim 1 , wherein: the content items are physical properties, the content-contributors provide indications of the properties to the content-distribution platform for reservation by the content-consumers for a duration of access, and the edges indicative of access of which ones of the content items by the content-consumers indicate which physical properties are reserved or duration of access completed by the content-consumers.
This invention relates to a content-distribution platform that manages access to physical properties by content-consumers. The system involves content-contributors who provide indications of available physical properties, which are then reserved by content-consumers for a specified duration. The platform tracks these reservations and access patterns, using edges in a data structure to represent which physical properties have been reserved or for which the access duration has been completed by the content-consumers. The system enables efficient allocation and monitoring of physical property access, ensuring that reservations are properly managed and durations are respected. The platform may also include mechanisms for content-consumers to request access, for the system to validate availability, and for the system to update access status based on reservation completion. This approach is particularly useful in scenarios where physical resources, such as equipment, facilities, or other tangible assets, need to be shared among multiple users in a controlled manner. The invention ensures that access is granted only when properties are available and that usage is tracked to prevent conflicts or overbooking.
19. The medium of claim 1 , wherein the burn address is not generated based on a public key having a known private key operable to generate a digital signature verifiable by the public key to transfer instances of cryptographic tokens to another address within the address space of the distributed computing platform.
This invention relates to cryptographic systems, specifically addressing privacy and security in distributed computing platforms that manage cryptographic tokens. The problem solved involves ensuring that certain addresses in the system cannot be linked to known private keys, preventing unauthorized tracking or control of token transfers. The invention describes a storage medium containing instructions for a distributed computing platform to manage cryptographic tokens. A key feature is the use of a "burn address," which is an address that cannot be generated from a public key associated with a known private key. Unlike standard addresses, this burn address cannot be used to create a verifiable digital signature required to transfer tokens to another address within the platform. This ensures that tokens sent to the burn address are effectively removed from circulation, enhancing privacy and security by preventing recovery or tracking through private key associations. The system includes mechanisms to generate and validate these burn addresses, ensuring they remain unlinkable to any known private key. This prevents malicious actors from exploiting private key knowledge to manipulate token transfers. The invention also includes methods to verify that a burn address is correctly implemented, ensuring its intended functionality is maintained. The overall solution provides a robust way to handle token disposal or irreversible transactions in a secure and private manner.
20. A computer-implemented method, the method comprising: obtaining a utilization graph, the utilization graph being based on which content-consumers access which content items, the utilization graph having: nodes indicative of respective ones of the content items available on a content-distribution platform, each of the content items being associated in memory with one of a plurality of different content-contributors credited with making the respective one of the content items available, and edges indicative of access of which ones of the content items by the content-consumers; selecting, from a distributed ledger of a distributed computing platform, a set of records indicative of transactions in which amounts of instances of a cryptographic token are transferred to a burn address of the distributed ledger, at least some transactions being associated with an indication of a respective content-consumer being permitted to access one or more of the content items as a result of a transaction; determining, based on the utilization graph, a network-effect score for each node in a set of nodes accessed by the content-consumers indicated in association with the at least some transactions in the set of records; determining, for each of at least some of the different content-contributors, an aggregate network-effect score for the content-contributor, the aggregate network-effect score being based on network-effect scores of nodes, in the set of nodes, corresponding to the respective ones of the content items the content-contributor is credited with making available; determining portions of an amount of new instances of the cryptographic token to allocate to the different content-contributors based on the respective aggregate network-effect scores; and causing, after determining the portions, the distributed computing platform to record, by appending to the distributed ledger, one or more records indicating that the respective portions of the amount of new instances of the cryptographic token are, or are to be, added to respective accounts documenting contributions of the respective content-contributor to the content-distribution platform.
This invention relates to a system for distributing cryptographic tokens to content-contributors on a content-distribution platform based on network effects. The problem addressed is the fair allocation of rewards to content-contributors whose content generates significant engagement, leveraging blockchain technology to ensure transparency and decentralization. The method involves analyzing a utilization graph that maps content-consumers to content items, where nodes represent content items and edges represent access patterns. The graph is used to calculate a network-effect score for each content item, reflecting its influence within the platform. A distributed ledger is queried to identify transactions where cryptographic tokens are burned (transferred to a burn address) in exchange for access to content. These transactions are linked to specific content-consumers, and the corresponding content items are evaluated using the utilization graph to determine their network-effect scores. For each content-contributor, an aggregate network-effect score is computed by summing the scores of all content items they are credited with. This aggregate score determines the proportion of newly minted tokens allocated to the contributor. The system then records these allocations on the distributed ledger, updating contributor accounts to reflect their contributions to the platform. The approach ensures that rewards are distributed based on measurable engagement and influence, incentivizing high-quality content creation.
21. The computer-implemented method of claim 20 , wherein: a plurality of nodes in the utilization graph are associated with a given content-contributor to credit the given content-contributor with making a corresponding plurality of the content items available; and nodes or edges are added to the utilization graph based on determinations that one or more of the corresponding plurality of the content items were each accessed for more than a threshold duration of time.
This invention relates to tracking and crediting content contributors in a digital content distribution system. The problem addressed is the lack of accurate attribution and compensation for contributors whose content is accessed by users, particularly when multiple contributors are involved in making content available. The solution involves a utilization graph that maps relationships between content items, contributors, and user access patterns to determine fair credit allocation. The utilization graph includes nodes representing content items and contributors, with edges indicating relationships between them. Contributors are credited for making content available, and the graph is dynamically updated based on user access data. Specifically, nodes or edges are added when a content item is accessed for more than a predefined threshold duration, ensuring that only meaningful interactions influence the graph. This helps distinguish between passive and active engagement, improving the accuracy of contributor attribution. The system may also track dependencies between content items, such as when one item references another, to further refine credit distribution. The goal is to provide a transparent and data-driven way to measure and reward contributor contributions based on actual usage.
22. The computer-implemented method of claim 20 , wherein: an edge between a pair of different ones of the nodes in the utilization graph indicates sequential access of respective ones of the content items during a session in which at least two of the content items were accessed by one of the content-consumers; the set of nodes accessed by the content-consumers indicated in association with the at least some transactions in the set of records comprises a first node corresponding to a first one of the at least two content items and a second node corresponding to a second one of the at least two content items; and determining network-effect scores of the first and second node comprises: determining a measure of network centrality of the first node relative to that of the other nodes in the set of nodes; and determining a measure of network centrality of the second node relative to that of the other nodes in the set of nodes.
This invention relates to analyzing content consumption patterns to determine the influence or importance of different content items within a network of user interactions. The problem addressed is identifying which content items have a significant impact on user behavior, particularly in sequential access patterns during sessions where multiple items are consumed. The method involves constructing a utilization graph where nodes represent content items and edges indicate sequential access by users during a session. For example, if a user accesses content item A followed by content item B, an edge connects the corresponding nodes. The system then analyzes this graph to compute network-effect scores for nodes, which quantify their centrality or influence relative to other nodes. Centrality measures, such as degree centrality or betweenness centrality, assess how frequently a node appears in sequences or acts as a bridge between other nodes. By comparing these scores, the system identifies which content items are most influential in driving user engagement or transitions to other content. This approach helps platforms optimize content recommendations, improve user retention, and identify high-value content by leveraging network analysis techniques to uncover hidden patterns in consumption behavior.
23. The computer-implemented method of claim 20 , wherein: the utilization graph indicates access of a subset of the content items by a plurality of the content consumers; the utilization graph is formed with operations comprising: obtaining a plurality of sequences in which respective ones of the plurality of the content-consumers accessed one or more of the content items in the subset; determining a transition probability matrix between the content items in the subset based on the plurality of sequences; and determining the edges of the utilization graph based on whether values of the transition probability matrix, or values based thereon, satisfy a threshold; and the aggregate network-effect score for a given content-contributor is representative of value added to the content-distribution platform by the given content-contributor among other ones of the content-contributors over at least the selected set of records.
This invention relates to analyzing content consumption patterns on a digital platform to evaluate the impact of individual content contributors. The problem addressed is quantifying the value added by specific contributors based on how their content influences user engagement across the platform. The method involves constructing a utilization graph that maps how users interact with content items. First, sequences of content access by multiple users are collected, showing the order in which users engage with different items. A transition probability matrix is then calculated, representing the likelihood of users moving from one content item to another. Edges in the utilization graph are established based on whether transition probabilities meet a predefined threshold, indicating significant connections between items. The graph is used to compute an aggregate network-effect score for each content contributor. This score reflects the contributor's overall impact on the platform by measuring how their content drives engagement with other content, distinguishing their value relative to other contributors. The analysis is performed over a selected set of records, ensuring the evaluation is based on relevant data. This approach helps platforms identify high-value contributors and optimize content distribution strategies.
24. The computer-implemented method of claim 20 , wherein: the utilization graph indicates access of a subset of the content items by a plurality of the content consumers; the utilization graph is formed with operations comprising: obtaining a plurality of records each indicating which ones of the content items were accessed by a respective one of the content-consumers; determining co-occurrence rates in the plurality of records, the co-occurrence rates indicating access of pairs of the content items indicated in the records; determining the edges of the utilization graph based on whether the co-occurrence rates or values based thereon satisfy a threshold; and the aggregate network-effect score for a given content-contributor is representative of value added to the content-distribution platform by the given content-contributor among other ones of the content-contributors over at least the selected set of records.
This invention relates to analyzing content consumption patterns on a content-distribution platform to assess the value of individual content contributors. The problem addressed is quantifying the impact of contributors by measuring how their content influences collective consumption behavior. The method involves constructing a utilization graph that maps relationships between content items based on co-occurrence in access patterns. Records are collected for each content consumer, detailing which content items they accessed. Co-occurrence rates are calculated for pairs of content items, indicating how frequently they are accessed together. These rates are used to determine edges in the utilization graph, where edges are formed if the co-occurrence rates or derived values meet a predefined threshold. The utilization graph visually represents how content items are interconnected through consumer access patterns. An aggregate network-effect score is then computed for each content contributor, reflecting their contribution to the platform's value relative to other contributors. This score is derived from the utilization graph and considers the broader impact of the contributor's content across the selected records. The approach enables platforms to identify high-value contributors by analyzing indirect relationships between content items, rather than relying solely on direct metrics like views or engagement. This helps optimize content curation and reward systems.
25. The computer-implemented method of claim 20 , further comprising: receiving a registration request from a computing device of a given content-contributor; establishing, in response to the registration request, a record of the given content contributor indicating a cryptographic hash based account of the given content-contributor to which a corresponding portion of the new instances of the cryptographic tokens are, or are to be, added; associating a given content item added to the content-distribution platform by the given content-contributor with the record of the content-contributor, wherein: the given content item is cryptographically signed with a private-cryptographic key of the given content-contributor before being uploaded to the content-distribution platform; and a given node corresponding to the given content item available on the content-distribution platform is caused to comprise an identifier indicative of the given content-contributor of the given content item after validating the cryptographic signature with a public cryptographic key associated with the identifier of the given content-contributor.
This invention relates to a content-distribution platform that uses cryptographic tokens and digital signatures to verify content contributors and their uploaded content. The system addresses the problem of ensuring the authenticity and traceability of digital content by leveraging cryptographic techniques to link contributors to their contributions. The method involves receiving a registration request from a content contributor's computing device and establishing a record for that contributor. This record includes a cryptographic hash-based account, which is used to track cryptographic tokens awarded to the contributor. When a contributor uploads a content item to the platform, the content is cryptographically signed using the contributor's private key before being uploaded. The platform then validates the signature using the contributor's public key, which is associated with their identifier. Once validated, the content item is linked to the contributor's record, and the contributor's identifier is included in the node representing the content on the platform. This ensures that the content's origin can be verified and traced back to the authenticated contributor. The system may also distribute cryptographic tokens to contributors as a form of reward or incentive for their contributions.
26. The computer-implemented method of claim 20 , wherein: the utilization graph is constructed based on utilization data indicative of access of a plurality of the content items over a network; and the operations further comprise: establishing nodes of the utilization graph based on identifiers of the plurality of the content items represented within the utilization data; establishing edges between pairs of at least some of the nodes within the utilization graph based on one or more sequences of occurrence of the identifiers; and scoring indications of access of each content item within the plurality of the content items by the computing device based on criteria satisfied by one or more of properties of the utilization data or properties inferred from the utilization data.
This invention relates to analyzing content access patterns over a network to identify relationships between content items. The problem addressed is the need to understand how users interact with digital content, such as web pages, documents, or media, to improve recommendations, security, or content organization. The method constructs a utilization graph representing content access patterns. Nodes in the graph correspond to content items, identified by unique identifiers extracted from network access data. Edges between nodes are established based on sequences in which content items are accessed, reflecting temporal or logical relationships. For example, if users frequently access content item A followed by content item B, an edge may be created between their corresponding nodes. The method also scores each content item based on criteria derived from the utilization data or inferred properties. Scoring may consider factors like access frequency, user engagement duration, or contextual metadata. These scores can prioritize content for recommendations, detect anomalies, or optimize content delivery. By analyzing the graph structure and access patterns, the system can infer relationships between content items that may not be explicitly defined, such as thematic connections or user navigation paths. This approach enables data-driven insights into content usage, improving personalized experiences or system performance.
27. The computer-implemented method of claim 20 , wherein determining a network score for each node in the set of nodes or an aggregate network score for each of the at least some of the different content-contributors comprises: determining a measure of network centrality based on an eigencentrality of corresponding nodes in the set of nodes determined with power iteration based on an adjacency matrix of the utilization graph.
This invention relates to analyzing network structures, specifically determining the influence or importance of nodes within a network by calculating network scores. The problem addressed is the need to quantify the centrality or importance of nodes in a network, such as social networks, content-sharing platforms, or other interconnected systems, to identify key contributors or influential entities. The method involves constructing a utilization graph representing relationships or interactions between nodes, where each node corresponds to a content-contributor or entity in the network. An adjacency matrix is derived from this graph, capturing the connections between nodes. Using power iteration, an eigencentrality measure is computed for each node, which reflects its importance based on its connections and the importance of its neighbors. This eigencentrality value is then used to determine a network score for individual nodes or an aggregate score for groups of nodes, such as different content-contributors. The approach leverages iterative matrix operations to efficiently compute centrality, providing a scalable way to assess node influence in large networks. The method can be applied to identify key influencers, optimize content distribution, or analyze network dynamics.
28. The computer-implemented method of claim 20 , wherein determining a network score for each node in the set of nodes or an aggregate network score for each of the at least some of the different content-contributors comprises: determining a measure of network centrality based on a percolation centrality of corresponding nodes in the set of nodes.
This invention relates to analyzing social or information networks to assess the influence or importance of nodes (e.g., users, content-contributors) within the network. The problem addressed is the need for a more accurate and robust method to quantify the centrality or influence of nodes in a network, particularly in scenarios where traditional centrality measures may be unreliable or computationally expensive. The method involves determining a network score for individual nodes or an aggregate score for groups of content-contributors. The key innovation is the use of percolation centrality to measure network centrality. Percolation centrality evaluates how critical a node is to the connectivity or flow of information within the network by assessing its role in maintaining or disrupting network percolation—a process where information or influence spreads through the network. This approach provides a more nuanced understanding of node importance compared to traditional metrics like degree centrality or betweenness centrality, as it accounts for the resilience and robustness of the network structure. The method can be applied to various network types, including social networks, communication networks, or content-sharing platforms, where understanding node influence is critical for tasks like identifying key influencers, detecting critical nodes for network stability, or optimizing information dissemination. The use of percolation centrality enhances the accuracy and reliability of network analysis, particularly in dynamic or noisy environments.
29. The computer-implemented method of claim 20 , wherein determining a network score for each node in the set of nodes or an aggregate network score for each of the at least some of the different content-contributors comprises: determining a measure of network centrality is based on node2Vec embeddings of corresponding nodes in the set of nodes.
This invention relates to analyzing social or information networks to assess the influence or importance of nodes (e.g., users, content-contributors) within the network. The problem addressed is the need for an effective way to quantify the centrality or influence of nodes in a network, which is useful for tasks like identifying key influencers, detecting spam, or improving content recommendations. The method involves calculating a network score for individual nodes or an aggregate score for groups of content-contributors. The key innovation is using node2Vec embeddings—a technique that generates vector representations of nodes based on their relationships in the network—to determine a measure of network centrality. Node2Vec embeddings capture both local and global network structures by simulating random walks through the network, allowing for a nuanced assessment of node importance beyond traditional metrics like degree centrality or betweenness centrality. By leveraging node2Vec embeddings, the method provides a more accurate and context-aware measure of node influence, which can be used to rank nodes, filter out low-influence contributors, or improve recommendation systems. The approach is particularly useful in large-scale networks where traditional centrality measures may be computationally expensive or less effective. The method can be applied in social media, recommendation systems, or any domain where understanding node influence is valuable.
30. The computer-implemented method of claim 20 , wherein: the network-effect score for each node in the set of nodes is based in part on content-consumer input scores of different ones of the content-consumers represented within the set of records; and a content-consumer input score of a given content-consumer is based in part on an amount of instances of the cryptographic token transferred to the burn address by one or more transactions associated with an indication of the given content-consumer.
This invention relates to a system for evaluating nodes in a network by analyzing cryptographic token transactions, particularly those involving a burn address. The problem addressed is the need to assess the influence or value of nodes in a network, such as content creators or consumers, based on verifiable, on-chain cryptographic activity. The method calculates a network-effect score for each node by incorporating content-consumer input scores derived from cryptographic token transactions. Specifically, a content-consumer's input score is determined by the quantity of cryptographic tokens they have transferred to a burn address, which is a designated address where tokens are permanently removed from circulation. Transactions associated with a given content-consumer are analyzed to count the instances of token transfers to the burn address, with higher transfer volumes indicating greater influence or engagement. This approach leverages blockchain data to provide a transparent and tamper-resistant measure of node activity, enabling more accurate network-effect scoring. The system can be applied to decentralized platforms, social networks, or other environments where cryptographic transactions influence node rankings or rewards.
31. The computer-implemented method of claim 30 , wherein a transaction associated an indication of the given content-consumer corresponds to: subscription access to the content-distribution platform by the given content-consumer, subscription access to a subset of content items on the content-distribution platform by the given content-consumer, or a purchase corresponding to one or more of the content items on the content-distribution platform by the given content-consumer.
A computer-implemented method for managing content access on a content-distribution platform involves tracking transactions associated with a content-consumer. The method determines whether a transaction corresponds to one of three types of access: full subscription access to the platform, subscription access to a subset of content items, or a purchase of one or more specific content items. This allows the platform to dynamically adjust access permissions based on the consumer's transaction history. The method may also involve verifying the consumer's identity, validating the transaction, and updating access rights accordingly. By distinguishing between different transaction types, the system ensures that consumers only access content they are authorized to view, whether through full subscription, partial subscription, or individual purchases. This approach enhances content security and prevents unauthorized access while providing flexibility in access management. The method may be integrated into a broader system for content distribution, ensuring seamless and secure content delivery based on transaction history.
32. The computer-implemented method of claim 20 , wherein appending one or more records to the distributed ledger in accordance with a consensus protocol executed by participant computing nodes of the distributed computing platform comprises: agreement upon a prior version of the distributed ledger comprising the set of records and other prior records by a majority of the participant computing nodes; and agreement upon a new version of the distributed ledger comprising the one or more appended records.
This invention relates to distributed ledger technology, specifically methods for appending records to a distributed ledger using a consensus protocol. The problem addressed is ensuring data integrity and consistency across multiple participant computing nodes in a distributed computing platform. The solution involves a consensus-based approach where participant nodes agree on the current state of the ledger before appending new records. The method begins by establishing agreement among a majority of participant computing nodes on a prior version of the distributed ledger, which includes a set of existing records and other previously recorded data. This ensures all nodes recognize the same baseline state before any updates. Once consensus is reached on the prior version, the nodes then agree on a new version of the ledger that includes the one or more newly appended records. This two-step consensus process prevents conflicts and ensures all nodes maintain an identical, up-to-date ledger. The consensus protocol enforces that changes to the ledger are only accepted if a majority of nodes approve both the prior state and the new state. This mechanism enhances security and reliability in distributed systems where nodes may operate independently or have varying levels of trust. The method is particularly useful in blockchain and other decentralized systems requiring tamper-proof record-keeping.
33. The computer-implemented method of claim 32 , wherein: agreement upon the new version of the distributed ledger is dependent on agreement upon the prior version and a plurality of other prior versions of the distributed ledger, an alteration of a given prior version of the distributed ledger renders a change in a cryptographic hash value based on the given prior version, and agreement upon the new version of the distributed ledger is dependent on verification that cryptographic hash values based on the prior versions are unchanged.
This invention relates to distributed ledger technology, specifically ensuring data integrity and consensus in a decentralized system. The problem addressed is maintaining consistency and trust in a distributed ledger when new versions are proposed, particularly when prior versions may have been altered. The solution involves a method where agreement on a new version of the distributed ledger depends on agreement on a prior version and multiple other prior versions. Any alteration to a prior version changes its cryptographic hash value, which is derived from that version. Agreement on the new version requires verifying that the cryptographic hash values of the prior versions remain unchanged, ensuring that no unauthorized modifications have occurred. This mechanism enforces a strict dependency chain, where the validity of the new version is contingent on the integrity of all referenced prior versions. The method enhances security by preventing tampering with historical data, as any alteration would invalidate the hash values, making consensus impossible. This approach is particularly useful in blockchain and other distributed ledger systems where immutability and consensus are critical.
34. The computer-implemented method of claim 20 , wherein appending to the distributed ledger in accordance with a consensus protocol executed by participant computing nodes of the distributed computing platform, one or more records indicating that the respective portions of the amount of new instances of the cryptographic token are, or are to be, added to respective accounts documenting contributions of the respective content-contributor to the content-distribution platform comprises: appending, by a script executed by one or more of the participant computing nodes of the decentralized computing platform, to the distributed ledger, the one or more records indicating the respective portions are transferred to the respective accounts by one or more transactions identifying respective cryptographic hash-based addresses of the content-contributors.
This invention relates to a decentralized computing platform that uses a distributed ledger to track contributions to a content-distribution platform. The problem addressed is ensuring transparent and verifiable documentation of contributions from content-contributors, where portions of newly issued cryptographic tokens are allocated to their accounts. The solution involves appending records to the distributed ledger using a consensus protocol executed by participant computing nodes. These records indicate that portions of the token amount are added to respective accounts, documenting each contributor's contributions. The process is automated by a script running on one or more participant nodes, which appends transactions to the ledger. Each transaction identifies the cryptographic hash-based addresses of the content-contributors, ensuring secure and traceable allocation of tokens. This method ensures that contributions are accurately recorded and verifiable within the decentralized system, maintaining transparency and trust in the platform. The use of cryptographic hashes and consensus protocols ensures that the ledger remains tamper-proof and reliable.
35. The computer-implemented method of claim 20 , wherein selecting, from a distributed ledger of a distributed computing platform, a set of records indicative of transactions in which amounts of instances of a cryptographic token are transferred to a burn address of the distributed ledger comprises: selecting a set of burn transactions associated with a current mint period of the cryptographic token from the set of records, the amount of new instances of the cryptographic token being minted for the current mint period in response to a determination that the set of burn transactions satisfy mint criteria for the current mint period, wherein: a burn transaction takes instances of the cryptographic token out of circulation by transferring the instances of cryptographic tokens to a burn address inoperable to transfer received instances of the cryptographic token to other addresses on the distributed computing platform, and the set of burn transactions associated with the current mint period have an aggregate score meeting or exceeding a target score for the current mint period based on amounts of instances of the cryptographic token being taken out of circulation in one or more prior mint periods.
This invention relates to a method for managing cryptographic tokens in a distributed ledger system, specifically focusing on token burning and minting mechanisms. The problem addressed involves ensuring controlled issuance of new tokens based on prior token burn activity, promoting scarcity and value stability. The method involves selecting a set of burn transactions from a distributed ledger, where these transactions transfer token instances to a burn address—a special address that permanently removes tokens from circulation. The selected burn transactions are associated with a current mint period and must collectively meet predefined mint criteria. A key aspect is that the aggregate score of these burn transactions, calculated based on the amount of tokens burned in prior periods, must meet or exceed a target score for the current period. This ensures that new token issuance is tied to historical burn activity, creating a feedback loop between token destruction and creation. The burn address is inoperable to transfer tokens, ensuring permanent removal from circulation. The minting of new tokens occurs only if the burn transactions satisfy the criteria, linking token supply directly to prior destruction activity. This mechanism aims to balance token supply and demand while maintaining transparency and predictability in token issuance.
36. The computer-implemented method of claim 20 , wherein: the content items are physical goods, the content-contributors provide the goods to the content-distribution platform, the content-distribution platform includes a delivery network in which drivers deliver physical goods to various geolocations to execute tasks assigned to the drivers by the content-distribution platform, the edges indicative of access of which ones of the content items by the content-consumers indicate which physical goods are delivered or scheduled for delivery to the content-consumers, and at least some network effect scores are determined for respective drivers based on an amount of tasks assigned to the drivers by the content-distribution platform.
This invention relates to a computer-implemented method for managing the distribution of physical goods through a content-distribution platform. The platform facilitates the delivery of goods from content-contributors to content-consumers via a delivery network, where drivers execute tasks assigned by the platform. The system tracks which goods are accessed or delivered to consumers, represented as edges in a network, and calculates network effect scores for drivers based on the volume of tasks they complete. These scores reflect the drivers' activity and efficiency within the distribution network. The platform optimizes delivery logistics by analyzing these scores and task assignments, ensuring timely and efficient distribution of physical goods. The method enhances the coordination between contributors, consumers, and drivers, improving overall delivery performance and resource utilization. The system may also prioritize tasks or adjust assignments based on driver performance metrics derived from the network effect scores. This approach streamlines the supply chain by leveraging data-driven insights to manage physical goods distribution effectively.
37. The computer-implemented method of claim 20 , wherein: the content items are physical properties, the content-contributors provide indications of the properties to the content-distribution platform for reservation by the content-consumers for a duration of access, and the edges indicative of access of which ones of the content items by the content-consumers indicate which physical properties are reserved or duration of access completed by the content-consumers.
This invention relates to a computer-implemented method for managing access to physical properties through a content-distribution platform. The system involves content-contributors who provide indications of available physical properties, which are then made accessible to content-consumers for reservation over a specified duration. The platform tracks access by content-consumers, recording which physical properties are reserved and the duration for which they are accessed. The method ensures that physical properties are allocated efficiently, preventing conflicts and ensuring that access is granted only for the reserved duration. The system may also include mechanisms to verify completion of access periods and update availability accordingly. This approach is particularly useful in scenarios where physical resources, such as equipment, spaces, or assets, need to be managed and allocated dynamically among multiple users. The method improves resource utilization by providing a structured way to reserve and track access, reducing scheduling conflicts and ensuring fair distribution. The platform may also include features to notify contributors and consumers about reservation status, access completion, and availability updates.
38. The computer-implemented method of claim 20 , wherein the burn address is not generated based on a public key having a known private key operable to generate a digital signature verifiable by the public key to transfer instances of cryptographic tokens to another address within the address space of the distributed computing platform.
This invention relates to cryptographic token management in distributed computing platforms, specifically addressing security risks associated with burn addresses. A burn address is a cryptographic address designed to permanently remove tokens from circulation by sending them to an unrecoverable location. The problem solved is the potential misuse of burn addresses that are generated using public keys with known private keys, which could allow unauthorized parties to create digital signatures to transfer tokens to other addresses within the platform. The invention ensures that burn addresses are generated without relying on such public-private key pairs, preventing unauthorized token transfers. This enhances security by eliminating the risk of tokens being redirected from the burn address to other addresses, ensuring tokens are irrevocably removed from circulation. The method involves generating a burn address that is cryptographically independent of any public key with a known private key, thereby preventing the generation of verifiable digital signatures that could facilitate unauthorized token transfers. This approach strengthens the integrity of token burn mechanisms in distributed computing platforms.
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February 5, 2020
March 15, 2022
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